ABSTRACT Fluorescent Speckle Microscopy (FSM) is an imaging mode to visualize and quantify the dynamics of macromolecular assemblies in living cells. It relies on vastly substoichiometric labeling of one or several components of the assembly of interest. When imaged by diffraction limited optics this labeling generates a random punctate texture that encodes in a statistical fashion transport, mechanical deformation, and molecular turnover of the assembly. As such, FSM is related to the super-resolution techniques STORM and PALM, which both rely also on random sampling of the molecular constituents of macromolecular assemblies. In STORM and PALM substochiometry in labeling is achieved by passive or active switching of a small set of fluorescent probes between a dark and a bright state. In contrast, in the original implementation FSM has relied on a population of permanently labeled subunits that dynamically incorporate in the assembly. In STORM and PALM, substochiometric labeling is exploited to sequentially collect the coordinates of individual subunits with nanometer precision, i.e. to acquire over time a super-resolution map of the molecular organization of an assembly. In FSM, substochiometric labeling is exploited to track in real-time subunit motion, addition and removal. Accordingly, the spatial resolution of FSM is still diffraction-limited; however, FSM offers information about the dynamics of a macromolecular assembly no other imaging modality provides. FSM has seen widespread applications in the research of cytoskeleton dynamics. Under the auspices of the present grant, my lab has developed the computational approaches required to make FSM a quantitative imaging technique (qFSM). In collaboration with several experimental groups as well as by developing FSM imaging capabilities in my own lab we have used qFSM technology to study the dynamics of the actin and microtubule cytoskeletons and associated molecular structures in cell morphogenesis, migration and division; and extended the method to the analysis of transient assembly of cell surface receptors in cellular signaling. Due to its rigid requirements for diffraction-limited imaging qFSM has been restricted, however, to live imaging of cells cultured on glass slides, which is entirely unphysiological. Capitalizing on the recent revolution in light-sheet imaging we propose here to take qFSM to the third dimension in order to apply its power for unveiling cytoskeleton dynamics in organotypic models of cells and tissues. This endeavor will require an iterative optimization of i) the design and implementation of multispectral light-sheet microscopy; ii) the flexible and simultaneous, substoichiometric labeling of multiple macromolecular assemblies, iii) the development of computational tools for tracking and interpretation of speckle dynamics in 3D time-lapse volumes. Specifically, in Aim 1, we will focus on molecular aggregates tracking microtubule plus ends and on clathrin-coated pits to develop fast 3D image acquisition and highly-sensitive 3D particle tracking methods with the goal of measuring the lifetime of macromolecular assemblies. In Aim 2, we will focus on the dynamics of the actomyosin cell cortex during cell polarization to develop robust dual-color speckle generation and optical-flow based computational methods with the goal of spatiotemporally mapping rates of molecular turnover and contraction in the cell cortical network. In Aim 3, we will focus on interactions between actomyosin cell cortex, components of cell adhesions, and the collagenous 3D microenvironment of cells to develop simultaneous 4- color image acquisition of speckle patterns and the computational tools for quantification and visualization of the coupled dynamics of macromolecular assemblies with the goal of testing the null hypothesis of a molecular clutch between cortical network and cell matrix adhesions in 3D. All tools will be engineered with an eye towards generalization, so that our technological innovations can be rapidly deployed to the community for the study of other dynamic cell structures.